Crop Disease Detection Using Deep Learning

In recent times, drastic climate changes and lack of immunity in crops has caused substantial increase in growth of crop diseases. This causes large scale demolition of crops, decreases cultivation and eventually leads to financial loss of farmers. Due to rapid growth in variety of diseases and adequate knowledge of farmer, identification and treatment of the disease has become a major challenge. The leaves have texture and visual similarities which attributes for identification of disease type. Hence, computer vision employed with deep learning provides the way to solve this problem. This paper proposes a deep learning-based model which is trained using public dataset containing images of healthy and diseased crop leaves. The model serves its objective by classifying images of leaves into diseased category based on the pattern of defect